DS-SLAM: A Semantic Visual SLAM towards Dynamic Environments. - Chao Yu 005; Zuxin Liu; Xin-Jun Liu; Fugui Xie; Yi Yang 039; Qi Wei 001; Fei Qiao (IROS, 2018)

Where Should We Place LiDARs on the Autonomous Vehicle? - An Optimal Design Approach. - Zuxin Liu; Mansur Arief; Ding Zhao (ICRA, 2019)

A DenseNet feature-based loop closure method for visual SLAM system. - Chao Yu 005; Zuxin Liu; Xin-Jun Liu; Fei Qiao; Yu Wang 002; Fugui Xie; Qi Wei 001; Yi Yang 039 (ROBIO, 2019)

MAPPER: Multi-Agent Path Planning with Evolutionary Reinforcement Learning in Mixed Dynamic Environments. - Zuxin Liu; Baiming Chen; Hongyi Zhou; Guru Koushik; Martial Hebert; Ding Zhao (IROS, 2020)

Task-Agnostic Online Reinforcement Learning with an Infinite Mixture of Gaussian Processes. - Mengdi Xu; Wenhao Ding; Jiacheng Zhu; Zuxin Liu; Baiming Chen; Ding Zhao (NeurIPS, 2020)

SAnE: Smart Annotation and Evaluation Tools for Point Cloud Data. - Hasan Asy'ari Arief; Mansur Arief; Guilin Zhang; Zuxin Liu; Manoj Bhat; Ulf Geir Indahl; Håvard Tveite; Ding Zhao (IEEE Access, 2020)

Delay-Aware Multi-Agent Reinforcement Learning. - Baiming Chen; Mengdi Xu; Zuxin Liu; Liang Li 004; Ding Zhao (CoRR, 2020)

Safe Model-based Reinforcement Learning with Robust Cross-Entropy Method. - Zuxin Liu; Hongyi Zhou; Baiming Chen; Sicheng Zhong; Martial Hebert; Ding Zhao (CoRR, 2020)

Context-Aware Safe Reinforcement Learning for Non-Stationary Environments. - Baiming Chen; Zuxin Liu; Jiacheng Zhu; Mengdi Xu; Wenhao Ding; Liang Li 004; Ding Zhao (ICRA, 2021)

Context-Aware Safe Reinforcement Learning for Non-Stationary Environments. - Baiming Chen; Zuxin Liu; Jiacheng Zhu; Mengdi Xu; Wenhao Ding; Ding Zhao (CoRR, 2021)

Improving Perception via Sensor Placement: Designing Multi-LiDAR Systems for Autonomous Vehicles. - Sharad Chitlangia; Zuxin Liu; Akhil Agnihotri; Ding Zhao (CoRR, 2021)

Robustness Certification of Visual Perception Models via Camera Motion Smoothing. - Hanjiang Hu; Zuxin Liu; Linyi Li 001; Jiacheng Zhu; Ding Zhao (CoRL, 2022)

Investigating the Impact of Multi-LiDAR Placement on Object Detection for Autonomous Driving. - Hanjiang Hu; Zuxin Liu; Sharad Chitlangia; Akhil Agnihotri; Ding Zhao (CVPR, 2022)

Constrained Variational Policy Optimization for Safe Reinforcement Learning. - Zuxin Liu; Zhepeng Cen; Vladislav Isenbaev; Wei Liu; Zhiwei Steven Wu; Bo Li 026; Ding Zhao (ICML, 2022)

SafeBench: A Benchmarking Platform for Safety Evaluation of Autonomous Vehicles. - Chejian Xu; Wenhao Ding; Weijie Lyu; Zuxin Liu; Shuai Wang; Yihan He; Hanjiang Hu; Ding Zhao; Bo Li 026 (NeurIPS, 2022)

Trustworthy Reinforcement Learning Against Intrinsic Vulnerabilities: Robustness, Safety, and Generalizability. - Mengdi Xu; Zuxin Liu; Peide Huang; Wenhao Ding; Zhepeng Cen; Bo Li 026; Ding Zhao (CoRR, 2022)

On the Robustness of Safe Reinforcement Learning under Observational Perturbations. - Zuxin Liu; Zijian Guo 002; Zhepeng Cen; Huan Zhang 001; Jie Tan 001; Bo Li 026; Ding Zhao (ICLR, 2023)

Towards Robust and Safe Reinforcement Learning with Benign Off-policy Data. - Zuxin Liu; Zijian Guo 002; Zhepeng Cen; Huan Zhang 001; Yihang Yao; Hanjiang Hu; Ding Zhao (ICML, 2023)

Constrained Decision Transformer for Offline Safe Reinforcement Learning. - Zuxin Liu; Zijian Guo 002; Yihang Yao; Zhepeng Cen; Wenhao Yu 003; Tingnan Zhang; Ding Zhao (ICML, 2023)

SeasonDepth: Cross-Season Monocular Depth Prediction Dataset and Benchmark Under Multiple Environments. - Hanjiang Hu; Baoquan Yang; Zhijian Qiao; Shiqi Liu 005; Jiacheng Zhu; Zuxin Liu; Wenhao Ding; Ding Zhao; Hesheng Wang 001 (IROS, 2023)

Learning Shared Safety Constraints from Multi-task Demonstrations. - Konwoo Kim; Gokul Swamy; Zuxin Liu; Ding Zhao; Sanjiban Choudhury; Zhiwei Steven Wu (NeurIPS, 2023)

Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning. - Yihang Yao; Zuxin Liu; Zhepeng Cen; Jiacheng Zhu; Wenhao Yu 003; Tingnan Zhang; Ding Zhao (NeurIPS, 2023)

Datasets and Benchmarks for Offline Safe Reinforcement Learning. - Zuxin Liu; Zijian Guo 002; Haohong Lin; Yihang Yao; Jiacheng Zhu; Zhepeng Cen; Hanjiang Hu; Wenhao Yu 003; Tingnan Zhang; Jie Tan 001; Ding Zhao (CoRR, 2023)

Influence of Camera-LiDAR Configuration on 3D Object Detection for Autonomous Driving. - Ye Li; Hanjiang Hu; Zuxin Liu; Ding Zhao (CoRR, 2023)

Safety-aware Causal Representation for Trustworthy Reinforcement Learning in Autonomous Driving. - Haohong Lin; Wenhao Ding; Zuxin Liu; Yaru Niu; Jiacheng Zhu; Yuming Niu; Ding Zhao (CoRR, 2023)

Pixel-wise Smoothing for Certified Robustness against Camera Motion Perturbations. - Hanjiang Hu; Zuxin Liu; Linyi Li 001; Jiacheng Zhu; Ding Zhao (AISTATS, 2024)

EXTRACT: Efficient Policy Learning by Extracting Transferable Robot Skills from Offline Data. - Jesse Zhang; Minho Heo; Zuxin Liu; Erdem Biyik; Joseph J. Lim; Yao Liu 009; Rasool Fakoor (CoRL, 2024)

Learning from Sparse Offline Datasets via Conservative Density Estimation. - Zhepeng Cen; Zuxin Liu; Zitong Wang 005; Yihang Yao; Henry Lam; Ding Zhao (ICLR, 2024)

TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models. - Zuxin Liu; Jesse Zhang; Kavosh Asadi; Yao Liu 009; Ding Zhao; Shoham Sabach; Rasool Fakoor (ICLR, 2024)

Feasibility Consistent Representation Learning for Safe Reinforcement Learning. - Zhepeng Cen; Yihang Yao; Zuxin Liu; Ding Zhao (ICML, 2024)

Influence of Camera-LiDAR Configuration on 3D Object Detection for Autonomous Driving. - Ye Li; Hanjiang Hu; Zuxin Liu; Xiaohao Xu; Xiaonan Huang; Ding Zhao (ICRA, 2024)

Reinforcement Learning in a Safety-Embedded MDP with Trajectory Optimization. - Fan Yang; Wenxuan Zhou; Zuxin Liu; Ding Zhao; David Held (ICRA, 2024)

Gradient shaping for multi-constraint safe reinforcement learning. - Yihang Yao; Zuxin Liu; Zhepeng Cen; Peide Huang; Tingnan Zhang; Wenhao Yu 003; Ding Zhao (L4DC, 2024)

APIGen: Automated PIpeline for Generating Verifiable and Diverse Function-Calling Datasets. - Zuxin Liu; Thai Hoang; Jianguo Zhang; Ming Zhu; Tian Lan; Shirley Kokane; Juntao Tan; Weiran Yao; Zhiwei Liu 001; Yihao Feng; Rithesh R. N.; Liangwei Yang; et al. (NeurIPS, 2024)

AgentOhana: Design Unified Data and Training Pipeline for Effective Agent Learning. - Jianguo Zhang 005; Tian Lan 006; Rithesh Murthy; Zhiwei Liu 001; Weiran Yao; Juntao Tan; Thai Hoang; Liangwei Yang; Yihao Feng; Zuxin Liu; Tulika Manoj Awalgaonkar; Juan Carlos Niebles; et al. (CoRR, 2024)

AgentLite: A Lightweight Library for Building and Advancing Task-Oriented LLM Agent System. - Zhiwei Liu 001; Weiran Yao; Jianguo Zhang 005; Liangwei Yang; Zuxin Liu; Juntao Tan; Prafulla Kumar Choubey; Tian Lan 006; Jason Wu; Huan Wang 014; Shelby Heinecke; Caiming Xiong; et al. (CoRR, 2024)

MobileAIBench: Benchmarking LLMs and LMMs for On-Device Use Cases. - Rithesh Murthy; Liangwei Yang; Juntao Tan; Tulika Manoj Awalgaonkar; Yilun Zhou; Shelby Heinecke; Sachin Desai; Jason Wu; Ran Xu 001; Sarah Tan; Jianguo Zhang 005; Zhiwei Liu 001; et al. (CoRR, 2024)

EXTRACT: Efficient Policy Learning by Extracting Transferrable Robot Skills from Offline Data. - Jesse Zhang; Minho Heo; Zuxin Liu; Erdem Biyik; Joseph J. Lim; Yao Liu 009; Rasool Fakoor (CoRR, 2024)

APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets. - Zuxin Liu; Thai Hoang; Jianguo Zhang 005; Ming Zhu; Tian Lan 006; Shirley Kokane; Juntao Tan; Weiran Yao; Zhiwei Liu 001; Yihao Feng; Rithesh Murthy; Liangwei Yang; et al. (CoRR, 2024)

Diversity Empowers Intelligence: Integrating Expertise of Software Engineering Agents. - Kexun Zhang; Weiran Yao; Zuxin Liu; Yihao Feng; Zhiwei Liu 001; Rithesh Murthy; Tian Lan 006; Lei Li 005; Renze Lou; Jiacheng Xu 001; Bo Pang 004; Yingbo Zhou; et al. (CoRR, 2024)

xLAM: A Family of Large Action Models to Empower AI Agent Systems. - Jianguo Zhang 005; Tian Lan 006; Ming Zhu; Zuxin Liu; Thai Hoang; Shirley Kokane; Weiran Yao; Juntao Tan; Akshara Prabhakar; Haolin Chen; Zhiwei Liu 001; Yihao Feng; et al. (CoRR, 2024)

PRACT: Optimizing Principled Reasoning and Acting of LLM Agent. - Zhiwei Liu 001; Weiran Yao; Jianguo Zhang 005; Rithesh Murthy; Liangwei Yang; Zuxin Liu; Tian Lan 006; Ming Zhu; Juntao Tan; Shirley Kokane; Thai Hoang; Juan Carlos Niebles; et al. (CoRR, 2024)

Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding. - Haolin Chen; Yihao Feng; Zuxin Liu; Weiran Yao; Akshara Prabhakar; Shelby Heinecke; Ricky Ho; Phil Mui; Silvio Savarese; Caiming Xiong; Huan Wang 014 (CoRR, 2024)

SpecTool: A Benchmark for Characterizing Errors in Tool-Use LLMs. - Shirley Kokane; Ming Zhu; Tulika Awalgaonkar; Jianguo Zhang; Thai Hoang; Akshara Prabhakar; Zuxin Liu; Tian Lan; Liangwei Yang; Juntao Tan; Rithesh Murthy; Weiran Yao; et al. (CoRR, 2024)

Safety-Aware Causal Representation for Trustworthy Offline Reinforcement Learning in Autonomous Driving. - Haohong Lin; Wenhao Ding; Zuxin Liu; Yaru Niu; Jiacheng Zhu; Yuming Niu; Ding Zhao (IEEE Robotics Autom. Lett., 2024)

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback. - Thai Quoc Hoang; Kung-Hsiang Huang; Shirley Kokane; Jianguo Zhang; Zuxin Liu; Ming Zhu; Jake Grigsby; Tian Lan; Michael S. Ryoo; Chien-Sheng Wu; Shelby Heinecke; Huan Wang 014; et al. (ACL (Findings), 2025)

PersonaBench: Evaluating AI Models on Understanding Personal Information through Accessing (Synthetic) Private User Data. - Juntao Tan; Liangwei Yang; Zuxin Liu; Zhiwei Liu 001; Rithesh R. N.; Tulika Manoj Awalgaonkar; Jianguo Zhang; Weiran Yao; Ming Zhu; Shirley Kokane; Silvio Savarese; Huan Wang 016; et al. (ACL (Findings), 2025)

Your Language Model May Think Too Rigidly: Achieving Reasoning Consistency with Symmetry-Enhanced Training. - Yihang Yao; Zhepeng Cen; Miao Li; William Han; Yuyou Zhang; Emerson Liu; Zuxin Liu; Chuang Gan 001; Ding Zhao (ACL (Findings), 2025)

Diversity Empowers Intelligence: Integrating Expertise of Software Engineering Agents. - Kexun Zhang; Weiran Yao; Zuxin Liu; Yihao Feng; Zhiwei Liu 001; Rithesh R. N.; Tian Lan 006; Lei Li 005; Renze Lou; Jiacheng Xu 001; Bo Pang 004; Yingbo Zhou; et al. (ICLR, 2025)

xLAM: A Family of Large Action Models to Empower AI Agent Systems. - Jianguo Zhang; Tian Lan 006; Ming Zhu; Zuxin Liu; Thai Hoang; Shirley Kokane; Weiran Yao; Juntao Tan; Akshara Prabhakar; Haolin Chen; Zhiwei Liu 001; Yihao Feng; et al. (NAACL (Long Papers), 2025)

PersonaBench: Evaluating AI Models on Understanding Personal Information through Accessing (Synthetic) Private User Data. - Juntao Tan; Liangwei Yang; Zuxin Liu; Zhiwei Liu 001; Rithesh Murthy; Tulika Manoj Awalgaonkar; Jianguo Zhang; Weiran Yao; Ming Zhu; Shirley Kokane; Silvio Savarese; Huan Wang 016; et al. (CoRR, 2025)

ActionStudio: A Lightweight Framework for Data and Training of Large Action Models. - Jianguo Zhang 005; Thai Hoang; Ming Zhu; Zuxin Liu; Shiyu Wang; Tulika Awalgaonkar; Akshara Prabhakar; Haolin Chen; Weiran Yao; Zhiwei Liu 001; Juntao Tan; Juan Carlos Niebles; et al. (CoRR, 2025)

APIGen-MT: Agentic Pipeline for Multi-Turn Data Generation via Simulated Agent-Human Interplay. - Akshara Prabhakar; Zuxin Liu; Ming Zhu; Jianguo Zhang 005; Tulika Awalgaonkar; Shiyu Wang; Zhiwei Liu 001; Haolin Chen; Thai Hoang; Juan Carlos Niebles; Shelby Heinecke; Weiran Yao; et al. (CoRR, 2025)

Behavior Injection: Preparing Language Models for Reinforcement Learning. - Zhepeng Cen; Yihang Yao; William Han; Zuxin Liu; Ding Zhao (CoRR, 2025)

MoDoMoDo: Multi-Domain Data Mixtures for Multimodal LLM Reinforcement Learning. - Yiqing Liang; Jielin Qiu; Wenhao Ding; Zuxin Liu; James Tompkin 001; Mengdi Xu; Mengzhou Xia; Zhengzhong Tu; Laixi Shi; Jiacheng Zhu (CoRR, 2025)

LAM SIMULATOR: Advancing Data Generation for Large Action Model Training via Online Exploration and Trajectory Feedback. - Thai Hoang; Kung-Hsiang Huang; Shirley Kokane; Jianguo Zhang 005; Zuxin Liu; Ming Zhu; Jake Grigsby; Tian Lan 006; Michael S. Ryoo; Chien-Sheng Wu; Shelby Heinecke; Huan Wang 014; et al. (CoRR, 2025)

MCPEval: Automatic MCP-based Deep Evaluation for AI Agent Models. - Zhiwei Liu 001; Jielin Qiu; Shiyu Wang; Jianguo Zhang 005; Zuxin Liu; Roshan Ram; Haolin Chen; Weiran Yao; Huan Wang 014; Shelby Heinecke; Silvio Savarese; Caiming Xiong (CoRR, 2025)

UserBench: An Interactive Gym Environment for User-Centric Agents. - Cheng Qian 008; Zuxin Liu; Akshara Prabhakar; Zhiwei Liu 001; Jianguo Zhang 005; Haolin Chen; Heng Ji 001; Weiran Yao; Shelby Heinecke; Silvio Savarese; Caiming Xiong; Huan Wang 014 (CoRR, 2025)